Data Literacy
Review and explore key principles of data analysis, before diving into advanced applications.
Free TrialLearning Plan Overview
- Understanding Data
- Introduction to Data Analytics
Introduction to Data and Databases
Data can deliver significant benefits to companies but is often not well understood by people. This course explains some key underlying principles of data, in three main sections: We’ll learn what structured data is, and how you can use it in data analysis We’ll learn how to obtain structured data, and how to convert data to a structured format. We’ll introduce several key concepts related to databases, which are a common data source used by many businesses.
Thinking and Communicating with Data
Data can bring value to modern companies, but there can be a disconnect between people in an organization who understand data and people who don’t. Data analysts may have good technical knowledge but might not understand the company as a whole. Non-data people may understand how the whole company works, but may struggle to get analysts to generate insights that meet their needs.
Principles of Statistics
Statistics is the process of collecting, analyzing and interpreting data. It underpins most work in data analytics. We can divide statistics into two broad areas: descriptive statistics and inferential statistics. Descriptive statistics focuses on summarizing a dataset of interest, so we can draw conclusions about the data. Inferential statistics involves making a prediction about a population of data based on a sample of that data.
Introduction to Predictive Modeling
In analytics, a model is a simplified mathematical approximation of some real-world process. We use models to identify relationships between fields or observations in a data set. When we create a good model, we should be able to use it to analyze other datasets or make predictions for the future.
